Neurosurgical retraction is a procedure that involves displacing brain tissue (i.e., to expose cancerous lesions). Current tools for retraction are mostly made of stainless steel and create localized regions of pressure. These tool-tissue interactions can be harmful and lead to postoperative complications. Research on soft robots is rapidly expanding due to their ability to safely interact with human tissue. Using principles of morphological computation, origami-inspired folding patterns have been developed to control the behavior of soft robots. However, for delicate brain tissue-tool interaction, greater control through the integration of soft sensing is required by surgeons. This work presents a pressure-actuated, origami-inspired soft robot with integrated sensing for measuring force during neurosurgical retraction procedures. The robot employs a circular Miura-origami (Miura-ori) pattern, creating well-defined contraction and expansion ratios. To embed a sensing modality in the robot, individual origami unit cells are modified to become flexible capacitors. These flexible Origami Sensing Modules (OSMs) change in capacitance when force is applied due to the displacement of capacitive plates. Surgeons can therefore monitor the procedure to ensure that dangerous levels of force are not exceeded. The OSM is fabricated using a layering technique that embeds a fluidic stiffening actuator within an elastomer dielectric. Thin copper films, which form the capacitive plates, sandwich this dielectric layer. Three OSMs, connected in series, are integrated into the circular Miura-ori pattern at evenly spaced locations. The force range and sensitivity of the OSMs are analyzed through force and motion characterization experiments which give an indication of the capacitive behavior during force application and actuation of the robot. Finally, an in-vitro setup was developed to model the retraction process in the brain and demonstrate the robot’s ability to retract brain tissue and sense the distributed forces. The development of this sensing mechanism allows for both monitoring and controlling the pressure on brain tissue during robotic retraction, demonstrating the potential of soft robots in neurosurgery. / 2025-08-29T00:00:00Z

The overarching purpose of this research is to understand whether Mixed Reality can enhance a surgeon’s manipulations skills during minimally invasive procedures. Minimally-invasive surgery (MIS) utilizes small cuts in the skin - or sometimes natural orifices - to deploy instruments inside a patient’s body, while a live video feed of the surgical site is provided by an endoscopic camera and displayed on a screen. MIS is associated with many benefits: small scars, less pain and shorter hospitalization time as compared to traditional open surgery. However, these benefits come at a cost: because surgeons have to work by looking at a monitor, and not down on their own hands, MIS disrupts their eye-hand coordination and makes even simple surgical maneuvers challenging to perform. In this study, we wish to use Mixed Reality technology to superimpose anatomical models over the surgical site and explore if it can be used to mitigate this problem.

Background: Pediatric minimally invasive surgery (MIS) is a standard technique worldwide. We aimed to analyze the research activity in this field. Methods: Articles on pediatric MIS (1991–2020) were analyzed from the Web of Science ™ for the total number of publications, citations, journals, and impact factors (IF). Of these, the 50 most cited publications were evaluated in detail and classified according to the level of evidence (i.e., study design) and topic (i.e., surgical procedure). Results: In total, 4464 publications and 53,111 citations from 684 journals on pediatric MIS were identified. The 50 most cited papers were published from 32 institutions in the USA/Canada (n = 28), Europe (n = 19 ), and Asia (n = 3) in 12 journals. Four authors (USA/Europe) contributed to 26% of the 50 most cited papers as first/senior author. Hot topics were laparoscopic pyeloplasty (n = 9), inguinal hernia repair (n = 7), appendectomy, and pyloromyotomy (n = 4 each). The majority of publications were retrospective studies (n = 33) and case reports (n = 6) (IF 5.2 ± 3.2; impact index 16.5 ± 6.4; citations 125 ± 39.4). They were cited as often as articles with high evidence levels (meta-analyses, n = 2; randomized controlled trials, n = 7; prospective studies, n = 2) (IF 12.9 ± 22.5; impact index 14.0 ± 6.5; citations 125 ± 34.7; p > 0.05). Conclusions: Publications on laparoscopic pyeloplasty, inguinal hernia repair, appendectomy, and pyloromyotomy are cited most often in pediatric MIS. However, the relevant number of studies with strong evidence for the advantages of MIS in pediatric surgery is missing

Yes / While Minimally Invasive Surgery (MIS) offers considerable benefits to patients, it also imposes big challenges on a surgeon's performance due to well-known issues and restrictions associated with the field of view (FOV), hand-eye misalignment and disorientation, as well as the lack of stereoscopic depth perception in monocular endoscopy. Augmented Reality (AR) technology can help to overcome these limitations by augmenting the real scene with annotations, labels, tumour measurements or even a 3D reconstruction of anatomy structures at the target surgical locations. However, previous research attempts of using AR technology in monocular MIS surgical scenes have been mainly focused on the information overlay without addressing correct spatial calibrations, which could lead to incorrect localization of annotations and labels, and inaccurate depth cues and tumour measurements. In this paper, we present a novel intra-operative dense surface reconstruction framework that is capable of providing geometry information from only monocular MIS videos for geometry-aware AR applications such as site measurements and depth cues. We address a number of compelling issues in augmenting a scene for a monocular MIS environment, such as drifting and inaccurate planar mapping. Methods A state-of-the-art Simultaneous Localization And Mapping (SLAM) algorithm used in robotics has been extended to deal with monocular MIS surgical scenes for reliable endoscopic camera tracking and salient point mapping. A robust global 3D surface reconstruction framework has been developed for building a dense surface using only unorganized sparse point clouds extracted from the SLAM. The 3D surface reconstruction framework employs the Moving Least Squares (MLS) smoothing algorithm and the Poisson surface reconstruction framework for real time processing of the point clouds data set. Finally, the 3D geometric information of the surgical scene allows better understanding and accurate placement AR augmentations based on a robust 3D calibration. Results We demonstrate the clinical relevance of our proposed system through two examples: a) measurement of the surface; b) depth cues in monocular endoscopy. The performance and accuracy evaluations of the proposed framework consist of two steps. First, we have created a computer-generated endoscopy simulation video to quantify the accuracy of the camera tracking by comparing the results of the video camera tracking with the recorded ground-truth camera trajectories. The accuracy of the surface reconstruction is assessed by evaluating the Root Mean Square Distance (RMSD) of surface vertices of the reconstructed mesh with that of the ground truth 3D models. An error of 1.24mm for the camera trajectories has been obtained and the RMSD for surface reconstruction is 2.54mm, which compare favourably with previous approaches. Second, \textit{in vivo} laparoscopic videos are used to examine the quality of accurate AR based annotation and measurement, and the creation of depth cues. These results show the potential promise of our geometry-aware AR technology to be used in MIS surgical scenes. Conclusions The results show that the new framework is robust and accurate in dealing with challenging situations such as the rapid endoscopy camera movements in monocular MIS scenes. Both camera tracking and surface reconstruction based on a sparse point cloud are effective and operated in real-time. This demonstrates the potential of our algorithm for accurate AR localization and depth augmentation with geometric cues and correct surface measurements in MIS with monocular endoscopes.

Stress in surgical environment is generally very high and can result in performance degradation increasing patient risk .Current Training systems for learning minimally invasive surgical skills do not consider the component of stress in their training model. In this study the focus was on developing alternative training models that would allow the learner to effectively perform minimally invasive skill under stress. Two alternate training methods: 1) Training under stress until high performance levels and 2) training until high performance and low cognitive load are achieved were considered for this study. The control group consisted of training under no stress and until high performance levels are achieved. Stressful environments for this study were simulated using physiologic stressors. The effectiveness of the training was evaluated by a comparative analysis of the different performance measures across the groups. We determined that training until automation as the most effective method to perform effectively under stress.

Arthroscopic knee surgery can be challenging because there is no intuitive relationship between the arthroscopic image, shown on a screen above the patient, and the camera in the surgeon's hand. As a result, arthroscopic surgeons require extensive training and experience. This thesis describes a computer system to help improve target acquisition in arthroscopy by visualizing the location and alignment of an arthroscope using augmented virtuality. A 3D computer model of the patient's joint (from CT) is shown, along with a model of the tracked arthroscopic probe and the projection of the camera image onto the virtual joint. We performed a user study to determine the effectiveness of this navigated display; the study showed that for novice residents, the navigated display improved target acquisition. However, residents with at least two years of experience performed worse. For surgeons, no effect on performance was found. / Thesis (Master, Computing) -- Queen's University, 2010-11-25 23:29:46.526

abstract: Needle steering is an extension of manually inserted needles that allows for maneuverability within the body in order to avoid anatomical obstacles and correct for undesired placement errors. Research into needle steering predominantly exploits interaction forces between a beveled tip and the medium, controlling the direction of forces by applying rotations at the base of the needle shaft in order to steer. These systems are either manually or robotically advanced, but have not achieved clinical relevance due to a multitude of limitations including compression effects in the shaft that cause undesired tissue slicing, torsional friction forces and deflection at tissue boundaries that create control difficulties, and a physical design that inherently restricts the workspace. While most improvements into these systems attempt to innovate the needle design or create tissue models to better understand interaction forces, this paper discusses a promising alternative: magnetic needle steering. Chapter 2 discusses an electromagnetic needle steering system that overcomes all aforementioned issues with traditional steering. The electromagnetic system advances the needle entirely magnetically so it does not encounter any compression or torsion effects, it can steer across tissue-interfaces at various angles of attack (90, 45, 22.5°) with root-mean-square error (RMSE) of 1.2 mm, achieve various radii of curvature as low as 10.2 mm with RMSE of 1.4 mm, and steer along complex 3D paths with RMSE as low as 0.4 mm. Although these results do effectively prove the viability of magnetic steering, the electromagnetic system is limited by a weak magnetic field and small 33mm cubic workspace. In order to overcome these limitations, the use of permanent magnets, which can achieve magnetic forces an order of magnitude larger than similarly sized electromagnetics, is investigated. The needle will be steered toward a permanent magnet configuration that is controlled by a 6 degree-of-freedom robotic manipulator. Three magnet configurations were investigated, two novel ideas that attempt to create local maximum points that stabilize the needle relative to the configuration, and one that pulls the needle toward a single magnet. Ultimately, the last design was found to be most viable to demonstrate the effectiveness of magnetic needle steering. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2020

To alleviate the poor ergonomics which surgeons suffer during knee arthroscopy, a semi-robotic device with braking mechanism is created for intraoperative assistance. A slitted ball joint assembly is developed to transmit the clamping force to the arthroscope inside. Ball deformation and stress at various angles to the vertical and clamping forces is recorded through Abaqus Finite Element Analysis (FEA). Contact forces between the scope and inner surfaces of the ball is also computed in FEA at different clamping forces. The von Mises stress occurring in the ball joint is under the yield stress limit for polyethylene, and there is noticeable force preventing the scope from sliding along the ball through-hole under clamping. A prototype of this device is constructed for proof-of-concept.

Local infiltration analgesia (LIA) is a new technique for postoperative pain management following knee arthroplasty. LIA involves a long-acting local anesthetic (ropivacaine), a non-steroid anti-inflammatory drug (ketorolac) and epinephrine infiltrated into the knee joint during surgery and injected postoperatively via a catheter. In the first two studies, LIA was compared with placebo in unicompartmental (I) and total (II) knee arthroplasty. Postoperative pain levels, morphine consumption and the incidence of side effects were lower in the LIA groups. In addition, we found a shorter length of hospital stay in the LIA group following unicompartmental knee arthroplasty compared with placebo (I), while the time to home readiness was shorter in the LIA group following total knee arthroplasty (II). In this study, we found that the unbound venous blood concentration of ropivacaine was below systemic toxic blood concentrations in a sub-group of patients. In the third study, LIA was compared with intrathecal morphine for postoperative pain relief following total knee arthroplasty (III). Pain scores and morphine consumption were lower, length of hospital stay was shorter and patient satisfaction was higher in the LIA group. In the final study, we investigated the effect of minimally invasive surgery (MIS) compared with conventional surgery in unicompartmental knee arthroplasty (IV). Both groups received LIA. We found no statistically significant differences in postoperative pain, morphine consumption, knee function, home readiness, hospital stay or patient satisfaction. In conclusion, LIA provided better postoperative pain relief and earlier mobilization than placebo, both in unicompartmental and total knee arthroplasty. When compared to intrathecal morphine, LIA also resulted in improved postoperative pain relief and earlier mobilization. Minimally invasive surgery did not improve outcomes after unicompartmental knee arthroplasty, when both groups received LIA.

Skills assessment in Minimally Invasive Surgery (MIS) has been a challenge for training centers for a long time. The emerging maturity of camera-based systems has the potential to transform problems into solutions in many different areas, including MIS. The current evaluation techniques for assessing the performance of surgeons and trainees are direct observation, global assessments, and checklists. These techniques are mostly subjective and can, therefore, involve a margin of bias. The current automated approaches are all implemented using mechanical or electromagnetic sensors, which suffer limitations and influence the surgeon’s motion. Thus, evaluating the skills of the MIS surgeons and trainees objectively has become an increasing concern. In this work, we integrate and coordinate multiple camera sensors to assess the performance of MIS trainees and surgeons. This study aims at developing an objective data-driven assessment that takes advantage of multiple coordinated sensors. The technical framework for the study is a synchronized network of sensors that captures large sets of measures from the training environment. The measures are then, processed to produce a reliable set of individual and composed metrics, coordinated in time, that suggest patterns of skill development. The sensors are non-invasive, real-time, and coordinated over many cues such as, eye movement, external shots of body and instruments, and internal shots of the operative field. The platform is validated by a case study of 17 subjects and 70 sessions. The results show that the platform output is highly accurate and reliable in detecting patterns of skills development and predicting the skill level of the trainees.